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What is short-termism?

Is it a buzzword or something that really impacts businesses in the economy?

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WBUR Podcast, Boston.

This is on point. I'm Megna Chakrabardi.

So the general understanding of how artificial intelligence models get trained is that they

scoop up vast amounts of data from the real world and learn how to create responses that match

that real world data.

Here's an example.

A large language model or LLM, tools that Siri or Alexa use to answer your questions.

In development, those LLMs read billions of text samples from across the Internet books, websites, etc.

The model looks for patterns on how words work together or really how humans use those words.

And as it trains, it tries to guess

maybe what word comes next in a sentence. And if it guesses wrong, it fixes the mistake,

it learns from that mistake. And then it repeats that process, billions and billions and

billions of time, each iteration getting better and better at better at guessing the right

word. That's essentially how the LLM learns to understand and write like a human. So what happens

when AI models run out of real-world data to train on.

Well, several research papers published in recent years suggest that developers will, in fact, run out of real-world data in a matter of years.

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